THE IMPLICATIONS OF PARAMETER UNCERTAINTY FOR FISCAL PLANNING
Doug Hostland and
David Dupuis
Additional contact information
David Dupuis: Department of Finance Canada
No 200, Computing in Economics and Finance 2000 from Society for Computational Economics
Abstract:
This paper investigates how parameter uncertainty affects the ability of the fiscal authority to attain its policy objectives. Our analysis is couched within a stochastic simulation framework wherein the fiscal authority seeks to control fluctuations in the debt / GDP ratio. The fiscal authority in our model responds to unanticipated economic developments by adjusting discretionary spending to bring the debt/GDP ratio back to its desired level. A high degree of debt control requires large and frequent discretionary changes and results in a pro-cyclical overall fiscal policy stance. The fiscal authority therefore faces a fundamental trade-off between its debt control objective and its other objectives, namely economic stabilisation and policy smoothing. In most existing stochastic simulation studies in this area (Boothe and Reid 1997; Hostland and Matier 1999; Dalsgaard and De Serres 1999), policy makers are given complete knowledge about the structure of the model. This unrealistic assumption is convenient for performing stochastic simulation experiments but might have nontrivial policy implications. In particular, a seminal paper by Brainard (1967) showed that uncertainty about the monetary policy transmission mechanism can change the optimal policy response in a simple static model. Several recent papers have examined this issue using dynamic models that are much more sophisticated than that originally considered by Brainard (Sack 1998; Martin 1999; Martin and Salman 1999; and Wieland 1999). This line of research indicates that parameter uncertainty generally gives rise to a more gradual monetary policy response. The purpose of this paper is to determine whether a similar conclusion can be drawn in the case of fiscal policy.
Date: 2000-07-05
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf0:200
Access Statistics for this paper
More papers in Computing in Economics and Finance 2000 from Society for Computational Economics CEF 2000, Departament d'Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 25,27, 08005, Barcelona, Spain. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().